Generic Abstract Linguistics

[winterkoninkje]

As the good Tom Waits would say, I want to pull on your coat about something. As I've been revamping my cv and hunting for advisors for the next round of phd applications, I've begun once again lamenting the fragmentation of my field. I suppose I should tell you what my field is but, y'see, that's where all the problems lie: there's no such field. As diverse and Renaissance as my interests are, they're all three sides of the same coin: language, sociality, and intelligence.

So, first things first. Evidently language is a diverse topic, but I mean to focus on formal and theoretical matters, the quintessence of what makes what we call "language". The early work of Chomsky to the contrary, there's an unfortunate —though entirely understandable— break between the study of formal languages and natural languages. On the natural side I'm interested in morphology and its interfaces with other components of language (morphophonology, morphosyntax & scrambling, morphosemantics & nuance). On the formal side I'm interested in the design of programming languages, ontologies, and interfaces. And on the middle side I'm interested in grammar formalisms like TAG and CCG as well as the automata theory that drives these and parsers and machine translation.

Sociality is also a diverse topic, without even accounting for the fact that I'm abusing the term to cover both the structure of societies and the interactions within and between them. Here too there's an unfortunate —though entirely understandable— break between the humanities and the sciences. In the humanities I'm interested in anthropology, gender/sexuality studies, performativity, the body as media, urban neo-tribalism, and online communities. More scientifically I'm interested in nonlinear systems theory, information theory, chaos theory, catastrophe theory, scale-free networks, and theoretical genetics. And again, on the middle side there are issues of sociolinguistics: code switching, emotional particles, uses of prosody, politeness and group-formation; and evolution: both evolutionary computation, and also cultural and linguistic evolution.

And as you may no doubt be gathering, studies of intelligence too are vast and harshly divided— between wetware and hardware, or between cognition and computation if you prefer. Language is often pegged as a fundamental component to humanity's ability for higher thought, and yet even despite this the majority of linguistic formalisms neglect questions of how cognitively realistic they are as models of actual human linguistic performance. Over on the side of artificial intelligence and artificial life there's a rift between those studying complexity, adaptation, and emergence vs those trying to hammer thought and knowledge into the rigid formalisms of logic and probability. Sandwiched between these conflicts are the war-torn battle grounds of machine translation, language learning, and language acquisition.

So how many fields are involved in this tripartite Janus of interfaces, systems, and agency? To make a short list: linguistics, mathematics, computer science, cultural anthropology, gender/queer/feminist studies, women's lit, systems science/systems theory, cognitive science, social psychology, computational biology, artificial intelligence/artificial life/machine learning, and given the vagaries of universities often electrical engineering and philosophy for good measure. How many is that? Too goddamned many, that's how many. And to top it off, all of them are interdisciplinary to boot. Now you may be saying to yourself that I'm trying too hard to unify too many disparate discourses, and perhaps it's true, but there is a cohesion there which should be evident by the extent to which each of those many fields crosscut these three seemingly simple categories.

To some extent I could just pick one extant field, but frankly they all get it wrong. Linguistics, my first love, is all too often uninterested in the computational tractability or cognitive reality behind the formalisms they advocate for capturing the hairy beast that is natural language. Computer science (the home of machine translation and parsing) and electrical engineering (the home of speech recognition) —though they've started coming around more recently— are all too often uninterested in theoretical linguistic issues, and even when individuals are interested the bulk of both departments focus on other topics more conventional to their fields (which is fine, but makes advisor hunting tricksy). Mathematics is fabulous, but all too often applied mathematicians, logicians, and semanticists operate under the misguided notion that the hairy beast can be quantified into the current state of mathematics, which even math-envious systems scientists are well aware is not the case; this is not to say there cannot be some formalism, just that it isn't here yet because the issues of conventional math and of natural language are very different, and that given my experience with this camp they're not willing to put aside current theories and create new ones more germane to this fuzzy illogical venue.

Nobody talks with anyone else. As I discussed above, linguists and computer scientists both despair of the other; granted computation linguistics and data mining are distant cousins with different goals, but both seek the same ability to understand language with computers. Even though NLP uses identical methodologies and faces profoundly similar problems as AI/ML, for some reason it takes decades for ideas to move from one community to the other. And the logical semanticists have at best cursory interaction with linguistic semanticists. Math envy runs high making interstitial interdisciplines like systems theory, machine learning, sociology, and the occasional linguist try desperately to distance themselves from philosophy, anthropology, and other disciplines deemed too soft, even though ideas originating in these fields form the basis of much of what those interdisciplines seek to capture.

Systems theory gets it right when they say that the current state of science is burdened by its focus on fundamentalism. Every field is focused on trying to drive things down, more basic, more primitive. And if computer science has taught us anything it's taught us that it's turtles all the way down; under applications are other applications, below those applications are operating systems, below those systems are languages, below languages are smaller languages, below them are smaller languages still, eventually is assembly that smallest language, and beneath that is machine language, beneath that the language of microcontrollers, the language of silicon circuits, down, down. It's often observed that biology can be reduced to chemistry, that chemistry can be reduced to physics. Like computer science, physics teaches us that there is no fundament; the molecules of chemical reactions become atoms, the nuclear atoms become protons, neutrons, electrons, the subatomic particles become quarks and quantum mechanics, down, down. And if physics can always unveil a smaller layer of physical reality, so too with formal ideas; computer science descends into mathematics, the sets and automata and topologies of mathematics descend into category theory which too always goes down, down.

But as Gell-Mann so eloquently stated, learning about the quark tells us nothing about the jaguar. If physics ever hits bottom, no matter how much we may one day learn about that fundamental mote of spatiotemporality, that knowledge cannot tell us anything of substance about the ways in which jaguars, or people, behave and interact; the reduction from one layer or representation to another looses information. What systems theory seeks to capture, as with my interest in generic abstract linguistics, is not the fundamental but rather the central, that which pertains at all levels of generality. No matter the level of abstraction, all of these layers exhibit the same or similar structures: they interact with a higher representation, they interact with a lower representation, and they interact with other systems within their layer. Systems theory tends to draw people from electrical engineering, computational biology, and artificial intelligence, but they have a message for computer scientists as well: the system and the interface are one. And there's a message for linguists too because language is just an interface, indeed language is precisely an embedding of the orator's system into the auditor's, every act of communication is an act of translation from one ontology into another. This message comes at us from philosophical anthropology as well: the speech is embedded in the dialogue, the act is embedded in a discourse, the discourse in society, and society in an intercultural exchange of ideas. Or if you prefer art and literature: the medium is the message.

There is something fundamentally central in my inter-interdisciplinary interests and it's that message about systems and language and emergence. As Kennedy and Eberhart say, the mind is social, it is not a solitary endeavor; intelligence arises out of a community of interaction. Language and culture are not defined by any one person, they are mutually defined by the interactions of many people, just as they are a description of the very same interactions of those people. Those familiar with Butler will be familiar with the idea that the act defines the self, rather than expressing it. The individual is defined by pushing off from the society, and in so doing defines that society as well as their own role in relation to it. The interaction defines the system, there is no self outside of society.

And yet, though I cite philosophers and artists and anthropologists, there is no reason why we cannot pursue a formal systematization of this fundamental centrality. Eberhart is an electrical engineer. Gell-Mann is a physicist. I'm emphatically not an engineer, but though I be a philosopher and theoretician, I am also an empiricist. This, I fear, is at the heart of my war. The gnosis is essential in the path to knowledge and wisdom, and yet it is too often discarded by those who work in mathematics and soulless circuitry. But if Sophia remained distant from the world there would be no hope for salvation; thought without action is meaningless. So too, without a formalization or systematization of our observations, even thought which pertains to the world is too often doomed to idle speculation. Nothing and everything can be said about postmodernity, this idle speculation too is thought without action, idea unbound from reality, from meaning.

Comments

[konomaigo.livejournal.com]

It sounds like you've given a lot of thought into what you want to study and why. Now you have to sell it to someone else.

This is always where I have trouble.

Good luck.

[winterkoninkje.livejournal.com]

Indeed, the trick is selling it.

It's good to hear from you, how've things been?

[qedragon.livejournal.com]

Not to be predictable, and I don't honestly know if it's the right answer, but I bet CMU would be willing to listen to your story. It was not rare, as I recall, for CS majors to dual in psychology and AFAIK the two departments do talk a great deal. (I've heard the CMU psych department criticized for being "too computational" in their approach.) The LTI and HCII at least claim to listen, too. :)

[winterkoninkje.livejournal.com]

Last I checked CMU was more cs/nlp-oriented than linguistics/cl, though it looks like there are a couple of morphosyntax folks (which is rare) and someone interested in Japanese (also rare) so it's worth another look.

[xuenay.livejournal.com]

I know what you mean. Often it seems to me like the worst problem in developing in real AI is that the knowledge required is too scattered over a dozen disciplines whcih aren't really talking to each other - often because in order to really "talk to the other", you'd need to spend a lot of time actually studying that field.

And when somebody does spend all that effort and manage to get an interdisciplinary paper published, it goes ignored because as a result of its interdisciplinary nature, others don't understand it. Gah.

[winterkoninkje.livejournal.com]

it goes ignored because as a result of its interdisciplinary nature, others don't understand it.

This is particularly a problem with computationally oriented linguistics. Many linguists these days realize the need/desire for using computers for large-scale empirical work, but few linguists actually know how to program or how to interpret the results of computational papers into the discussion of linguistics.

Edinburgh has a number of good folks in this regard (and a number of very linguistically-minded folks over in cogsci/informatics), so I'm thinking I might head off to Scotland if they'll have me. I've been meaning to leave the country anyways, and Edinburgh is looking a bit more linguistic than Hong Kong (and the missus'll like somewhere she can speak the language...)